Update README.md

README.md

@@ -172,4 +172,30 @@ license: cc-by-4.0
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 # Dataset Card for "dreambooth"
 
-[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+## Dataset of the Google paper DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generation
+
+The dataset includes 30 subjects of 15 different classes. 9 out of these subjects are live subjects (dogs and cats) and 21 are objects. The dataset contains a variable number of images per subject (4-6). Images of the subjects are usually captured in different conditions, environments and under different angles.
+
+We include a file dataset/prompts\_and\_classes.txt which contains all of the prompts used in the paper for live subjects and objects, as well as the class name used for the subjects.
+
+The images have either been captured by the paper authors, or sourced from www.unsplash.com
+
+The dataset/references\_and\_licenses.txt file contains a list of all the reference links to the images in www.unsplash.com - and attribution to the photographer, along with the license of the image.
+
+### [project page](https://dreambooth.github.io/) | [arxiv](https://arxiv.org/abs/2208.12242)
+
+## Academic Citation
+
+If you use this work please cite:
+```
+@inproceedings{ruiz2023dreambooth,
+ title={Dreambooth: Fine tuning text-to-image diffusion models for subject-driven generation},
+ author={Ruiz, Nataniel and Li, Yuanzhen and Jampani, Varun and Pritch, Yael and Rubinstein, Michael and Aberman, Kfir},
+ booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
+ year={2023}
+}
+```
+
+## Disclaimer
+
+This is not an officially supported Google product.